CN108983288A - Grease recognition methods based on time-frequency spectrum image characteristic analysis - Google Patents
Grease recognition methods based on time-frequency spectrum image characteristic analysis Download PDFInfo
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Abstract
The invention proposes a kind of grease recognition methods based on time-frequency spectrum image characteristic analysis, comprising the following steps: step S10: extracting the seismic data of the well point purpose reservoir of grease property to be identified, carries out spectral signal analysis to seismic data.According to spectrum distribution range and earthquake dominant frequency, the time-frequency spectral power distribution of well seismic channel was obtained using match tracing time-frequency spectrum image analysis technology；Step S20: time-frequency spectrum is normalized；Step S30: the fluid-filled property in Reservoir Body is identified according to time-frequency spectrum characteristics of image in time interval corresponding to purpose reservoir in well point in time-frequency spectrum.When being identified using the method in the present invention to the fluid-filled property in carbonate fracture and cave reservoir, fluid identification result and actual production well coincide, and rate is high, and the structure for analyzing fluid-filled property in the Reservoir Body of identification carbonate reservoir using time-frequency feature is reliable.
Description
Technical field
It is fluid-filled based on earthquake Time-frequency Spectrum Analysis identification ultra deep carbonate rock fractured cave Reservoir Body that the present invention relates to one kind
The method of property belongs to the grease identification field in geophysical prospecting for oil.
Background technique
For the fluid identification of oil-bearing reservoir, domestic and foreign scholars have conducted extensive research in sandstone reservoir, but are directed to
The fluid identification of carbonate reservoir is still in the exploratory development stage.Domestic scholars are directed to the area BL Changxing Group stratum carbonate rock
Reef flat facies lithologic deposit, which has, buries the non-uniform feature of depth, petroleum distribution, stores up with viscid diffusion-type wave equation simulation
Layer seismic response features identify reservoir gas-bearing property using frequency attenuation gradient attribute and low frequency companion shadow phenomenon.There are also researchers
Carried out the fluid identification of reservoir research based on spectrum signature difference, with high band amplitude difference feature be according to identification cave with
Collapsing-filling cave fluid properties.
Seismic properties are applied to currently based on the technology that matching pursuit algorithm carries out the decomposed and reconstituted decomposition of seismic signal
In the every field of analysis and research, there is scholar to carry out sparse point to seismic signal using the MP algorithm based on Ricker wavelet atom
Solution, and then can realize the high-precision wave impedance inversion to underground geologic bodies, separately have and the algorithm is used for instantaneous spectrum discrimination to determine
Delta sandbody pinch-out boundary, and the inverting of peak instantaneous frequency thin layer is carried out using MP spectral factorization algorithm, while carrying out gassiness storage
The hydrocarbon indication of layer.
Firstly, the existing fluid identification of reservoir technology based on Prestack seismic data it is computationally intensive, to data requirement height.And
In carbonate rock fractured cave type Reservoir Body, the main body of oil reservoir is larger fluid-filled solution cavity, and the stream in large-scale cave
Body does not propagate shear wave, the effective elasticity parameter as recognizing oil, gas and water in sandstone reservoir can not be extracted, such as P- and S-wave velocity and bullet
Property modulus etc., therefore the application of pre-stack elastic inversion technology is restricted.In addition, based on the recognition methods of seismic attributes analysis by
The influence of many factors such as buried depth of strata, lithology, thickness, temperature, pressure, multi-solution is stronger, the rock physics meaning of operation result
Justice is not clear enough, explains that difficulty is larger.
Summary of the invention
In view of the above technical problems, the invention proposes a kind of grease identification sides based on time-frequency spectrum image characteristic analysis
Method, comprising the following steps:
Step S10: extracting the seismic data of the well point purpose reservoir of grease property to be identified, carries out frequency spectrum to seismic data
Signal analysis.According to spectrum distribution range and earthquake dominant frequency, with obtaining well using match tracing time-frequency spectrum image analysis technology
Shake the time-frequency spectral power distribution in road；
Step S20: time-frequency spectrum is normalized；
Step S30: known according to time-frequency spectrum characteristics of image in time interval corresponding to purpose reservoir in well point in time-frequency spectrum
Fluid-filled property in other Reservoir Body.
In a specific embodiment, when the time-frequency spectrum picture in the time interval is in the direction reduced towards frequency
The arch of protrusion, and the frequency of the time-frequency spectrum in this time interval is less than dominant frequency, then and the well point purpose reservoir preserves
Fluid oil content in body is higher than water content.
In a specific embodiment, when the time-frequency spectrum picture in the time interval is in the direction increased towards frequency
The arch of protrusion, and the frequency of the time-frequency spectrum in this time interval is greater than dominant frequency, then and the well point purpose reservoir preserves
Fluid water content in body is higher than oil content.
In a specific embodiment, when the time-frequency spectrum picture in the time interval to high frequency direction migrate, and
The frequency of time-frequency spectrum in this time interval is greater than 30Hz, then not aqueous in the Reservoir Body of the well point purpose reservoir to be also free of
Oil.
In a specific embodiment, when the time-frequency spectrum picture in the time interval is along the direction for being parallel to time shaft
Extend, and the frequency of the time-frequency spectrum in this time interval is greater than 30Hz, then does not have Reservoir Body development in the reservoir.
In a specific embodiment, step S10 includes step S01~S03,
Step S01: sparse decomposition is carried out to seismic signal, constructs dictionary matrix D；
Step S02: using matching pursuit algorithm, and the atom seismic signal function y upright projection to dictionary matrix D is enterprising
The duplicate iterative estimation of row, until residual value signal is less than or equal to preset threshold value, by the linear of the atom being iterated and
Seismic signal is indicated along with last residual values；
Step S03: indicate that seismic signal is distributed using time-frequency spectrum.
In a specific embodiment, in step 20, each vector in time-frequency spectrum | | xi| |=1.
In a specific embodiment, dominant frequency 25Hz.
When being identified using the method in the present invention to the fluid-filled property in carbonate fracture and cave reservoir, fluid is known
Other result and the identical rate of actual production well are high, analyze fluid in the Reservoir Body of identification carbonate reservoir using time-frequency feature and fill
The structure for filling out property is reliable.
Detailed description of the invention
The invention will be described in more detail below based on embodiments and refering to the accompanying drawings.Wherein:
Fig. 1 is the process of the grease recognition methods based on time-frequency spectrum image characteristic analysis in one embodiment of the present of invention
Figure；
Fig. 2 is the frequency spectrum profile of well point target zone seismic data in one embodiment of the present of invention；
Fig. 3 is the time-frequency two-dimensional spectrogram for the well seismic channel excessively not being normalized in one embodiment of the present of invention
Picture；
Fig. 4 is the time-frequency two-dimensional spectrogram picture for crossing well seismic channel that normalized is completed in one embodiment of the present of invention；
Fig. 5 is to show the time-frequency feature of the higher reservoir of oil content in Reservoir Body in one embodiment of the present of invention
Time-frequency spectrum picture；
Fig. 6 is to show the time-frequency feature of the higher reservoir of water content in Reservoir Body in one embodiment of the present of invention
Time-frequency spectrum picture；
Fig. 7 is that the time-frequency spectrum of the time-frequency feature of the reservoir without Reservoir Body is shown in one embodiment of the present of invention
Picture；
Fig. 8 be one embodiment of the present of invention in show the low reservoir of Reservoir Body development degree time-frequency feature when
Spectral image.
In the accompanying drawings, identical component uses identical appended drawing reference.The attached drawing is not drawn according to the actual ratio.
Specific embodiment
The present invention will be further described with reference to the accompanying drawings.
Fig. 1 shows the grease recognition methods based on time-frequency spectrum image characteristic analysis in one embodiment of the present of invention
Flow chart, the grease recognition methods fluid-filled property in carbonate fracture and cave reservoir for identification.The grease recognition methods
The following steps are included:
Step S10: extracting the seismic data of the well point purpose reservoir of grease property to be identified, carries out frequency spectrum to seismic data
Signal analysis.According to spectrum distribution range and earthquake dominant frequency, with obtaining well using match tracing time-frequency spectrum image analysis technology
Shake the time-frequency spectral power distribution in road.Step S10 includes step S01~S03.
The spectrum distribution situation of the well point reservoir for showing system in Tahe Oilfield in Fig. 2, the well point reservoir frequency spectrum of system in Tahe Oilfield
Range is 5-70Hz, dominant frequency 25Hz.
Step S01: sparse decomposition is carried out to seismic signal, constructs dictionary matrix D.
Dictionary matrix D is the function set carried out after original signal sparse decomposition.The method for constructing dictionary matrix D is ability
The prior art in domain, details are not described herein.In the present embodiment, by well point purpose seismic reservoir signal function y using one group to
Measure { x1,x2,x3,...xnIndicate, the length for the seismic signal being expressed is n, this group of vector constitutes dictionary matrix D.Dictionary
Each vector x in matrix D is an atom.Amplitude, centre time, peak frequencies of each atom as the wavelet corresponding to it
It is indicated with the four-dimensional vector that phase is constituted.The length of atom is identical as the length n of seismic signal y being expressed.
Step S02: using matching pursuit algorithm, and the atom seismic signal function y upright projection to dictionary matrix D is enterprising
The duplicate iterative estimation of row, until residual value signal is less than or equal to preset threshold value, by the linear of the atom being iterated and
Seismic signal is indicated along with last residual values.
Selection one matches optimal time-frequency atom linear combination with original signal, constructs a sparse bayesian learning, and find out
Signal residual error R then proceedes to selection and the most matched atom of signal residual error, iterates, seismic signal y is by these atoms come line
Property and, indicated along with last residual values.
Given matching criterior termination condition parameter, i.e., if residual values are within preset threshold value, seismic signal y is exactly
The linear combination of the atom.
The expression formula of seismic signal function y are as follows:
Y=< y, xn>xn+Rmy (1)
(1) in formula, y is well point purpose seismic reservoir signal function；<y,xn> it is original signal y and selected atom when iteration
XnInner product；RmY is the residual values of the m times iteration.
It is all first to find out and the maximally related atom x of original signal in each iterative processn, in order to make < y, xn>xnWith original
Beginning, signal y was most approached, residual values RmY is as small as possible, inner product item < y, xn> answer it is as big as possible.Match tracing is superior adaptive with its
Answer feature, using with the good time, frequency resolution when-frequency atom pair seismic signal constantly looks for best match, really
Accurately ground-to-ground shake signal carries out Time-frequency Decomposition, reduces the interference of cross term in frequency spectrum.
Step S03: indicate that seismic signal is distributed using time-frequency spectrum.
One-dimensional time signal is transformed into two-dimensional T/F plane, can preferably reflect seismic signal in this way
Time-frequency characteristics.
Step S20: time-frequency spectrum is normalized.
Each time-frequency spectral sequence is normalized, i.e., by each vector in time-frequency spectrum | | xi| |=1.By
When differently seismic wave-frequency reaction peak value difference.As shown in figure 3, existing Time-frequency Spectrum Analysis is characterized as the display side of energy group
Formula, when m- scale plane on the time-frequency distributions be unfolded, relationship indigestion between scale and frequency is not easy to identification point
Analysis.
In the present embodiment, two-dimentional time-frequency spectrum is normalized, i.e., time-frequency spectrum is returned using following formula
One changes conversion:
(2) in formula, XminFor the minimum value in sample, XmaxFor the maximum value in sample.
As shown in figure 4, the two-dimensional spectrum after normalization can describe simultaneously continuous and discrete time letter on frequency coordinate axis
Number frequency modified-image, convenient for identification frequency range, determine the reservoir frequency limit value filled with different fluid.
Step S30: known according to time-frequency spectrum characteristics of image in time interval corresponding to purpose reservoir in well point in time-frequency spectrum
Fluid-filled property in other Reservoir Body.
In Fig. 5~8, time interval corresponding to the purpose reservoir of well point is T74 to the part between T74+60ms.
As shown in figure 5, when the time-frequency spectrum picture in the time interval is in the arch of the direction protrusion reduced towards frequency,
And the frequency of the time-frequency spectrum in this time interval is less than dominant frequency, then the fluid in the Reservoir Body of the well point purpose reservoir contains
Oil mass is higher than water content.
Oil content refers to that the volume of Reservoir Body Crude Oil accounts for the percentage of fluid volume；Water content refers to underground in Reservoir Body
The volume of water accounts for the percentage of fluid volume.
As shown in fig. 6, when the time-frequency spectrum picture in the time interval is in the arch of the direction protrusion increased towards frequency,
And the frequency of the time-frequency spectrum in this time interval is greater than dominant frequency, then the fluid in the Reservoir Body of the well point purpose reservoir contains
Water is higher than oil content.
As shown in fig. 7, when the time-frequency spectrum picture in the time interval is migrated to high frequency direction, and in this time interval
The frequency of interior time-frequency spectrum is greater than 30Hz, then not aqueous also not oil-containing in the Reservoir Body of the well point purpose reservoir.
As shown in figure 8, when the time-frequency spectrum picture in the time interval extends along the direction for being parallel to time shaft, and
The frequency of time-frequency spectrum in this time section is greater than 30Hz, then does not have Reservoir Body development in the reservoir.
It can predict whether contain fluid and fluid properties to drilling well purpose reservoir using this method, can be used for instructing to give birth to
It produces.
Comparative example 1
Grease property identification is carried out to the fluid in the Reservoir Body in Tahe ultra deep carbonate reservoir using this method
When, first the grease property in multiple well point purpose reservoirs is identified, then with 247 mouthfuls of wells being drilled through in the oil reservoir region
Well-log information is verified.Wherein, it is believed that fluid oil content in Reservoir Body is 86% than the identical rate of high-moisture situation,
The identical rate for thinking the situation higher than oil content of the fluid water content in the Reservoir Body of the reservoir is 68.4%, it is believed that is not had in reservoir
There is Reservoir Body and the low identical rate of Reservoir Body development degree is 76.9%.Above-mentioned statistics does not account for acid fracturing after boring, large-scale pressure
The service shafts such as split and fill the water.Fluid identification result and the identical rate of actual production well are high, should be the result shows that utilizing time-frequency feature point
Grease property is reliable in the Reservoir Body of analysis identification carbonate reservoir.
Comparative example 2
As shown in table 1, the feasibility that Tahe Ordovician system fracture and cave reservoir fluid properties are detected for verifying spectral properties, according to
9 mouthfuls of well location coordinates and substantially finishing drilling depth to drilling well judge to carry out prediction before drilling using based on time-frequency spectrum image characteristic analysis
The validity of fracture and cave reservoir fluid oiliness.Final 9 mouthfuls of wells are according to frequency spectrum limits criteria and the complete well of fluid detection prediction of result
Reservoir Section oil-producing situation afterwards, 7 mouthfuls of wells meet reservoir fluid testing result, reach satisfied result.
1 prediction before drilling of table and actual production Comparative result
Although by reference to preferred embodiment, invention has been described, the case where not departing from the scope of the present invention
Under, various improvement can be carried out to it and can replace component therein with equivalent.Especially, as long as there is no structures to rush
Prominent, items technical characteristic mentioned in the various embodiments can be combined in any way.The invention is not limited to texts
Disclosed in specific embodiment, but include all technical solutions falling within the scope of the claims.
Claims (9)
1. a kind of grease recognition methods based on time-frequency spectrum image characteristic analysis, comprising the following steps:
Step S10: extracting the seismic data of the well point purpose reservoir of grease property to be identified, carries out spectrum signal to seismic data
Analysis, according to spectrum distribution range and earthquake dominant frequency, obtained well seismic channel using match tracing time-frequency spectrum image analysis technology
Time-frequency spectral power distribution；
Step S20: time-frequency spectrum is normalized；
Step S30: storage is identified according to time-frequency spectrum characteristics of image in time interval corresponding to purpose reservoir in well point in time-frequency spectrum
Fluid-filled property in collective.
2. grease recognition methods according to claim 1, which is characterized in that when the time-frequency spectrum picture in the time interval
In the arch of the direction protrusion reduced towards frequency, and the frequency of the time-frequency spectrum in this time interval is less than dominant frequency, then institute
The fluid oil content stated in the Reservoir Body of well point purpose reservoir is higher than water content.
3. grease recognition methods according to claim 1, which is characterized in that when the time-frequency spectrum picture in the time interval
In the arch of the direction protrusion increased towards frequency, and the frequency of the time-frequency spectrum in this time interval is greater than dominant frequency, then institute
The fluid water content stated in the Reservoir Body of well point purpose reservoir is higher than oil content.
4. grease recognition methods according to claim 1, which is characterized in that when the time-frequency spectrum picture in the time interval
It is migrated to high frequency direction, and the frequency of the time-frequency spectrum in this time interval is greater than 30Hz, then the well point purpose reservoir
Not aqueous also not oil-containing in Reservoir Body.
5. grease recognition methods according to claim 1, which is characterized in that when the time-frequency spectrum picture in the time interval
Extend along the direction for being parallel to time shaft, and the frequency of the time-frequency spectrum in this time interval is greater than 30Hz, then in the reservoir
There is no Reservoir Body development.
6. grease recognition methods according to any one of claim 1 to 5, which is characterized in that step S10 includes step
S01~S03,
Step S01: sparse decomposition is carried out to seismic signal, constructs dictionary matrix D；
Step S02: matching pursuit algorithm is used, weight is carried out on the atom seismic signal function y upright projection to dictionary matrix D
Multiple iterative estimation adds by the linear of the atom being iterated and again until residual value signal is less than or equal to preset threshold value
Last residual values are gone up to indicate seismic signal；
Step S03: indicate that seismic signal is distributed using time-frequency spectrum.
7. grease recognition methods according to any one of claim 1 to 5, which is characterized in that in step 20, time-frequency spectrum
In each vector | | xi| |=1.
8. grease recognition methods according to any one of claim 1 to 5, which is characterized in that the grease recognition methods
Fluid-filled property in carbonate fracture and cave reservoir for identification.
9. the grease recognition methods according to Claims 2 or 3, which is characterized in that the dominant frequency is 25Hz.
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